Text Analytics

Text Analytics in Big Data Analytics

It analyse the content of the text
the text data is considered here which explains the freelancers profile and the rate / hour in term of US Dollars
The concept is fixing a model which offers the skills of freelancer and needed to forecast their salary in hourly basis
the underlying code demonstrates the way to change the raw data i.e. skills of clients in a set of text or word matrix form
To achieve this, tm (R library) is employed
It refers that for every word in the data , it is required to generate variable with the count of appearances of every variable

To get a sparse solution , it is needed to fix a model to represent text as a sparse matrix
An another substitute for this scenario is employing Least Absolute Shrinkage and Selection Operator shortly noted as LASSO
It is a regression model which chooses the key applicable features to forecast the target

This is model which forecasts an hourly salary of a freelancer once the collection of skills is offered
When more data is gathered, the resultant performance of the model will increase
The code to deploy this stream will be same